Using Document Structure in Matching of Projected Slides

Abstract

[[abstract]]This thesis proposes an image matching algorithm for matching up video document images against original documents. Our approach extracts the text and picture regions from the document, then build structure description to match up the original document without reconstructing the background. This makes original documents be manufactured with different background. The algorithm consists of four steps. First, the document content is segmented from the video and calibrated to the video frame size. We named the document content video document. Second, the video document is processed by document analysis, then the text and picture regions are extracted. Third, the text and picture region are used to build structure description individually. Finally, we calculate the confident value between the video document and each original document, and take the one which have the highest confident value to be the matching result. Experiments were conducted using fifty-one sets of slides and video files, and the number of all slides is 1153. We use the proposed algorithm to match up the video frame against the corresponding slide. The experimental results attain 97.4% precision rate in total slides. This shows the algorithm can be applied to the low quality video and slides with composite contents.